A generalized framework that simplifies Targeted Learning by identifying and implementing a series of common statistical estimation procedures.
A common interface and engine that accommodates current algorithmic approaches to Targeted Learning and is still flexible enough to remain the engine even as new techniques are developed.
A generalized framework for flexible cross-validation.
Cross-validation is a key part of ensuring error estimates are honest and preventing overfitting. It is an essential part of both the Super Learner algorithm and Targeted Learning.
Not all treatment variables are discrete. Being able to estimate the effects of continuous treatment represents a powerful extension of the Targeted Learning approach.
Other Free Software
ltmle: Longitudinal Targeted Maximum Likelihood Estimation
Targeted Maximum Likelihood Estimation (TMLE) of treatment/censoring specific mean outcome or marginal structural model for point-treatment and longitudinal data.